Citation: | YANG Yan, ZHANG Dexin, YUE Huiet al. Image fusion dehazing algorithm based on minimum channel and logarithmic attenuation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(10): 1844-1852. doi: 10.13700/j.bh.1001-5965.2019.0552(in Chinese) |
The image color degradation and blurred details acquired by various image acquisition systems in foggy weather seriously affect the stability and effectiveness of outdoor imaging system, so it is necessary to study image dehazing technology. Aimed at the incomplete edge dehazing of dark channel dehazing algorithm, a fusion dehazing method based on the minimum channel and logarithmic attenuation is proposed. Firstly, the logarithmic attenuation of the minimum channel map of the foggy image is taken as a priori hypothesis, and then cross-bilateral filtering is performed to eliminate the texture effect. Before and after the operation, downsampling and upsampling operations are performed respectively to improve the operation speed, then we get the initial transmittance. Secondly, Canny operator is used to detect the edge of the minimum channel and logarithmic attenuation is carried out to obtain the edge information map. The initial transmittance and the edge information map are weighted and fused to compose the optimal transmittance. Finally, the atmospheric light value obtained by the improved quadtree search method is used to solve the atmospheric scattering model and restore the fog-free image. The experimental results demonstrate that the proposed algorithm can effectively suppress halo effect and remove edge residual fog, and has good real-time performance.
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